The invention has applications in radio-frequency receivers, in particular mobile stations or fixed stations of a radiocommunication system, for example a Private Mobile Radiocommunication (PMR) system. In such an application, the signal to be converted is for example a signal containing 20 or so channels each having a bandwidth of about 12 kHz (kilohertz), that is a signal occupying a frequency band of total bandwidth of about 200 kHz.
Sigma-Delta converters are very widely used in the field of analog-to-digital conversion because of their high resolution (quantization is typically carried out on 16 bits, and even on 17 or 18 bits in some cases). This high resolution is achieved by having a sampling frequency that is high compared with the band of the converted signal (typically, the sampling frequency is around 1 megahertz or around 10 megahertz), which does not constitute a drawback in a radio-frequency system.
The principle of a Sigma-Delta modulator is illustrated by the diagram of FIG. 1. This figure represents a low-pass Sigma-Delta modulator 100 through which an analog input signal's samples x(nT), obtained at a determined sampling frequency denoted Fs from now on, can be converted to values y(nT) of a digital output signal encoded on n bits, where n is an integer.
The converter 100 includes an analog subtractor 11 the positive input of which receives the samples x(nT), and the negative input of which receives the samples x′(nT) of an analog feedback signal. The output of the subtractor 11 is used as input to a filter 12, the output of which is connected to the input of an analog-to-digital converter 10, from now on referred to as ADC. A feedback loop includes a digital-to-analog converter 20, from now on referred to as DAC, which receives at its input the values y(nT) of the digital output signal and converts them in order to deliver the samples x′(nT) of the abovementioned analog feedback signal.
In a low-pass Sigma-Delta analog-to-digital converter, which is suitable for the analog-to-digital conversion of a baseband signal, the filter 12 is a low-pass filter. The latter performs noise shaping, enabling quantization noise to be rejected in the higher frequencies.
Noise shaping by a first-order low-pass filter is illustrated by the graph of FIG. 2. This figure represents the energy density N of the quantization noise as a function of frequency f, for values of f between 0 and Fs. The higher the order of the filter, the greater the energy density rejected in the higher frequencies.
Thus connected, the ADC converts not the samples x(nT) of the input signal directly but the difference between these samples x(nT) and samples x′(nT) of the analog feedback signal, after noise shaping by the filter 12.
The quantization noise is then eliminated by digital post-processing by means of a decimation filter (not represented) receiving at its input the values y(nT) of the digital output signal encoded on n bits, and delivering at its output digital values encoded on n+m bits where m is also an integer. The post-processing by the decimation filter brings about a low-pass filtering in order to attenuate the energy of the signal outside the useful band. It also has the function of bringing the sampling frequency back to the Nyquist frequency, for example by performing an average over several consecutive values of the output signal y(nT). For a low-pass Sigma-Delta analog-to-digital converter, the noise shaping function corresponds to the inverse of a sine cardinal function (“sinc” function), such that the transfer function of the decimation filter is a sinc function which is easy to realize.
If the converter is produced using CMOS technology components, which generate noise at a frequency of zero (DC frequency), it is preferable not to perform the conversion of the baseband signal. The signal is converted after frequency translation to a frequency band of between, for example, 400 kHz and 600 kHz. The signal to be converted is then centered on a center frequency Fo, equal to 500 kHz in this example. Noise shaping by the low-pass filter of the converter then becomes a drawback, since the energy density of the quantization noise at the frequency Fo may be high, which significantly degrades the signal-to-noise ratio (SNR).
This is why there is a need for bandpass Sigma-Delta analog-to-digital converters.
The principle of a bandpass Sigma-Delta converter 200 is illustrated by the diagram of FIG. 3, in which the same items as in FIG. 1 bear the same references. Substantially, this principle is similar to that of the low-pass Sigma-Delta converter 100, the noise-shaping low-pass filter 12 of the latter (FIG. 1) being replaced however with a resonator 13. It is recalled that a resonator is a bandpass filtering cell having infinite gain at a determined frequency (corresponding to a pole of the transfer function) called the center frequency of the resonator. The center frequency of the resonator 13 is set to the center frequency Fo of the frequency band of the signal to be converted.
Noise shaping by a first-order resonator is illustrated by the graph of FIG. 4, to be compared with that of FIG. 2. As can be seen in this figure, the quantization noise is rejected on either side of the center frequency Fo. The higher the order of the filter, the greater the quantization noise energy density thus rejected.
In practice, the center frequency Fo of the band of the signal to be converted is set up to be Fs/4, in which case one refers to the “Fs/4 mode” of the converter. The return to baseband at the output of the converter (upstream of the decimation filter) is then provided by simple digital calculation operations, since it is a matter of multiplying by the four values 1, 0, −1 and 0.
Examples of such converters are proposed for example in reference U.S. Pat. No. 5,383,578. In this document, implementations are proposed in which the converter includes two first- or second-order resonators in series, each having their center frequency set to the center frequency Fo of the frequency band of the signal to be converted.
An important parameter of a bandpass Sigma-Delta converter is the width of the frequency band around the center frequency of the resonator, outside of which the quantization noise is rejected. This parameter is important because it directly affects the SNR. The greater the width, the better the SNR.
In the prior art, there are two techniques currently known for increasing the width of this band:                either the sampling frequency Fs is increased, by arranging, for example, for the center frequency Fo of the band of the signal to be converted to be equal to Fs/8 (in which case one refers to the “Fs/8 mode” of the converter); this amounts to increasing the OverSampling Ratio (OSR), but in that case there are restrictions due to the characteristics of the amplifier used to produce the converter;        or the order of the converter is increased, which requires the use of particular structures, the most current of which is the MASH type cascaded structure (see “Oversampling Delta-Sigma Data Converters—Theory, Design and Simulation”, Candy et al., IEEE Press, 1992), in order to work around the stability problems; examples of converters thus having several cascaded stages (called “MASH Sigma-Delta converters”) are shown for example in the abovementioned U.S. Pat. No. 5,383,578.        